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Graph Databases: Neo4j, RDF, Knowledge Graphs & GraphRAG (Udemy.com)

Learn Neo4j with Python and Cypher, GraphQL, Knowledge Graphs, RDF, Graph Algorithms, LangChain, GraphRAG from Scratch

Created by: Aritra Basak

Last updated August 2026

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What you will learn

  • You will understand the fundamentals of graph databases and how they differ from traditional databases.
  • You will learn how to use Neo4j, write Cypher queries, and work with graph data using Python.
  • You will apply graph algorithms like BFS, DFS, and shortest path to solve real-world problems.
  • You will build knowledge graphs and understand RDF, SPARQL, GraphQL, and GraphRAG concepts.
  • You will learn to develop RAG workflows with LangChain.

How it compares

Against the other 388 rated Udemy courses in SQL on CourseDuck:

  • Rating4.4 out of 5higher than 34% of them
  • Reviews102#349 of 389 by number of reviews
  • Length12.8 hourslonger than 81% of them
  • Last updatedAugust 2026more recently than 92% of them

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Course Description

Welcome to the Complete Graph Databases Course

This course is a complete, beginner to advanced guide to graph databases. You will learn how modern systems use graphs to model complex relationships and how to build real world applications using Neo4j, Python, RDF, knowledge graphs, and GraphRAG.

What You Will Learn

• Understand what graph databases are and how they differ from relational databases
• Learn graph theory concepts like nodes, relationships, directed graphs, cyclic graphs, and DAGs
• Work confidently with Neo4j and write efficient Cypher queries
• Use Python to create pipelines and automate graph data workflows
• Apply graph algorithms such as BFS, DFS, shortest path, and Dijkstra’s algorithm
• Learn RDF, SPARQL, GraphQL, knowledge graphs, RAG Pipelines with LangChain and GraphRAG

Course Highlights

• Beginner friendly explanations with visual learning
• Hands on Neo4j and Python integration
• Real world projects including routing systems and fraud detection
• Coverage of both property graphs and semantic graphs
• Modern AI concepts like knowledge graphs, RAG and GraphRAG
• Practical focus with code and real use cases

Who This Course Is For

• Beginners who want to learn graph databases from scratch
• Software developers and backend engineers
• Data engineers and data scientists
• AI and machine learning engineers interested in knowledge graphs
• Anyone curious about graph based systems and modern data architectures

Why Enroll

Graph databases are increasingly used in areas like recommendation systems, fraud detection, social networks, and AI powered applications. This course gives you a structured learning path with practical skills that you can directly apply to real world problems, projects, and jobs.


By the end of this course, you will have a strong understanding of graph databases and the confidence to work with Neo4j, Python, graph algorithms, RDF, knowledge graphs, and GraphRAG in real world applications.

Enroll now and start mastering graph databases step by step.

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Instructor Details

Aritra Basak

Hi, I’m Aritra a senior software engineer with years of experience at a leading Big Tech firm, where I built scalable systems and explored the frontier of machine learning and generative AI. My passion lies not just in building intelligent systems, but in making complex ideas feel simple, visual, and intuitive.

As an educator, I specialize in breaking down advanced technical concepts into easy-to-understand lessons using diagrams, analogies, and real-world hooks. Whether it’s neural networks, transformers, or architectural design patterns, I believe every learner deserves clarity and a touch of creativity.

Join me on Udemy to master the tools and thinking behind modern AI and software engineering, with courses designed to empower you from the ground up.


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Reviews

4.4

102 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Francisco Freitas on 9/24/2026

Great course! However, I think the code for Section 14 should be included directly here rather than placed in a separate course, as it covers a core topic of this course.

By Goktug Peker on 9/24/2026

The course provides a good balance of practical and theoretical knowledge. The best part comes toward the end, and overall, the course is well structured. However, the scope of the course could be explained more clearly at the beginning, especially since the most valuable content for producing scalable AI orchestration is covered toward the end.

By Navneet Setia on 9/21/2026

overall i like the course but there were points like auto code completion, which as a beginner i want to know why we write that specific code for newer technology. Overall it was nice

By Lalitha on 8/12/2026

excellent teaching making complex things simple

By Boris Rudakov on 7/18/2026

For God's sake, if your handwriting is terrible, just type. Why on earth are you referencing Python internals in this section? How is that supposed to help anyone understand the subject? Bottom line: if you actually want to understand this topic, it's much cleaner to just ask an AI. Don't waste your time here.

By Shakti Shwetanshu on 7/13/2026

Crisp and to the point presentation and teaching. I love it.

By Joshua David Bradley on 7/1/2026

Easy to understand and follow. Visuals / examples help with real world application right out of the box

By Sajitha Dissanayake on 6/11/2026

The course is really good to get a basic understanding on the Knowledge graph concepts. I would like to see more information on the graph rag section

By Mei-Jiuan Juang on 2/5/2026

I like this course so far. I have took 15 lessons. One thing disappointing is the instructor hand writing the whiteboard takes really long time. Why not prepare slides instead? Watching you handwriting every thing is really inefficient. 50% of time can be saved for every student if you use slides instead.

By Debi Sen on 12/21/2025

I thoroughly enjoy Aritra's teaching style. His clear explanations, visual aids, and use of simple, practical examples make complex topics easy to understand. This course on graph databases was exceptionally well structured and insightful. Highly recommended for anyone looking to deepen their understanding of the subject.

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Overall Score : 88 / 100